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A new class of energy-efficient digital microprocessor is being developedwhich is susceptible to thermal noise and consequently operates inprobabilistic rather than conventional deterministic mode. Hybrid computingsystems which combine probabilistic and deterministic processors can providerobust and efficient tools for computational problems that hitherto would beintractable by conventional deterministic algorithm. These developments suggesta revised perspective on the consequences of ion-channel noise in slenderaxons, often regarded as a hindrance to neuronal computations. It is proposedthat the human brain is such an energy-efficient hybrid computational systemwhose remarkable characteristics emerge from constructive synergies betweenprobabilistic and deterministic modes of operation. In particular, the capacityfor intuition and creative problem solving appears to arise naturally from sucha hybrid system. Bearing in mind that physical thermal noise is both pure andavailable at no cost, our proposal has implications for attempts to emulate theenergy-efficient human brain on conventional energy-intensive deterministicsupercomputers.

Neuronal noise as a physical resource for human cognition